Software Alternatives, Accelerators & Startups
Register | Login

python xlrd VS bokeh python

Compare python xlrd VS bokeh python and see what are their differences

Modelence
Create production-ready applications with zero code featured
Contents:
  1. ยป Base Details
  2. ยป Reviews
  3. ยป Alternatives

python xlrd logo python xlrd

Please use openpyxl where you can... Contribute to python-excel/xlrd development by creating an account on GitHub.

bokeh python logo bokeh python

This Python tutorial will get you up and running with Bokeh, using examples and a real-world dataset. You'll learn how to visualize your data, customize and organize your visualizations, and add interactivity.
  • python xlrd Landing page
    Landing page //
    2023-08-18
  • bokeh python Landing page
    Landing page //
    2023-08-18

python xlrd features and specs

  • Simplicity
    xlrd provides a straightforward and easy-to-use API for reading Excel files, making it accessible for beginners and quick implementations.
  • Widely Used
    xlrd has been a popular choice for handling Excel files in Python, which means there is a lot of available documentation and community support.
  • Efficient Reading
    It is optimized for reading data from Excel files without loading entire data into memory, which is beneficial for handling large files.

Possible disadvantages of python xlrd

  • No Write Support
    xlrd is designed solely for reading, and it does not support writing or modifying Excel files.
  • Limited to Older Excel Formats
    With version 2.0 and above, xlrd only supports the older .xls Excel file format and does not support .xlsx files.
  • Deprecated Features
    Due to changes in dependencies and updates to Excel formats, some features in xlrd have become deprecated or removed, which can limit its functionality.

bokeh python features and specs

  • Interactivity
    Bokeh provides interactive plots and dashboards that can enhance the user experience by allowing them to explore data by zooming, panning, and hovering.
  • Web Integration
    It generates outputs that are readily usable in web applications. Bokeh plots can be embedded in web pages, making it suitable for creating dashboards and web-based data visualization applications.
  • Versatility
    Bokeh supports a wide variety of plots and chart types, which allows users to create complex and informative visualizations.
  • Pythonic Syntax
    The library has an API that is intuitive for Python users, making it easier to learn and integrate into Python-based projects.
  • Server for Real-time Updates
    Bokeh server allows for the creation of interactive, real-time streaming web applications, which is useful for applications requiring live data updates.

Possible disadvantages of bokeh python

  • Learning Curve
    Despite its intuitive syntax, Bokeh's extensive capabilities and features can present a steeper learning curve, particularly for beginners in data visualization.
  • Rendering Performance
    For very large datasets, Bokeh might encounter performance issues, such as slower rendering times in the browser compared to other digital visualization technologies.
  • Limited 3D Capabilities
    Unlike some other visualization libraries, Bokehโ€™s support for 3D plotting is limited, which might be a constraint for users needing advanced 3D plotting features.
  • Complexity with Advanced Plots
    While Bokeh is great for basic plots, creating highly customized or advanced visualizations may require more effort, with users potentially needing to write custom JavaScript callbacks.
  • Dependencies
    Bokehโ€™s reliance on JavaScript and other underlying libraries might pose challenges in environments where managing dependencies is complex.

Category Popularity

0-100% (relative to python xlrd and bokeh python)

python xlrd

bokeh python

Application Builder
54 54%
Application Builder
46% 46
Development Tools
54 54%
Development Tools
46% 46
Data Science And Machine Learning
54 54%
Data Science And Machine Learning
46% 46
Game Development
50 50%
Game Development
50% 50

User comments

Share your experience with using python xlrd and bokeh python. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, python xlrd seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

python xlrd mentions (2)

  • I need to read multiple excel files, extract a column from each and compose a new file
    So to get this out of the way first, xlrd has less features than openpyxl and in addition only works with the old '.xls' format, not the newer '.xlsx' format. Even on the xlrd's Github repo it says: 'Please use openpyxl where you can... '. Source: over 4 years ago
  • Sending Bulk SMS using Africas Talking, Python and Excel
    There are few alternative libraries for reading and writing excel files: Pandas, Xlrd , openpyxl among others. In the end I settled for openpyxl as I had the most experience Using it and it had support for .xlsx files. - Source: dev.to / over 5 years ago

bokeh python mentions (0)

We have not tracked any mentions of bokeh python yet. Tracking of bokeh python recommendations started around Mar 2021.

What are some alternatives?

When comparing python xlrd and bokeh python, you can also consider the following products

Ionic - Ionic is a cross-platform mobile development stack for building performant apps on all platforms with open web technologies.

Flutter - Build beautiful native apps in record time ๐Ÿš€

python pillow - The friendly PIL fork (Python Imaging Library). Contribute to python-pillow/Pillow development by creating an account on GitHub.

Telerik - UI Frameworks and App Development Tools

python docx - Create and modify Word documents with Python. Contribute to python-openxml/python-docx development by creating an account on GitHub.

Material UI - A CSS Framework and a Set of React Components that Implement Google's Material Design

Loading...